Teaching AI Ethics and Sustainability Through Everyday Questions

Artificial intelligence (AI) can help with tasks such as sorting information or recognising patterns. But it is also worth asking what happens when people use it: Does it treat people fairly? What information does it rely on? Could its use affect the environment?

These questions are part of AI literacy: understanding AI well enough to use it thoughtfully and question its effects. Students do not need to build an AI system to begin exploring these ideas. Careful discussion, simple sorting activities and everyday examples can help them practise.

What the source tells us

The Raspberry Pi Foundation describes a UK research study focused on teaching AI ethics and sustainability to lower-secondary students. Its literature review found that teaching activities often address fairness and privacy, while topics such as governance and proportionality appear less often. It also found that direct teaching about AI’s environmental impact was uncommon. The study aims to explore teaching approaches that support ethical reasoning, critical thinking and student agency.

The study is for computing teachers in England, Scotland and Wales; it is not an Indian programme. The activities below are practical suggestions for Indian students, parents and teachers, not findings from that study or a claim about any particular curriculum.

Start with three questions

When a tool or service uses AI, invite students to pause and ask:

• Who is affected? Consider the person using the tool and anyone it may make a decision about.
• What information is involved? Is the information personal, incomplete or possibly incorrect?
• What might be the wider effect? Could the system save time, cause harm or use resources that have an environmental cost?

There may not be one easy answer. The aim is to identify what is known, what is uncertain and what else should be checked.

Suggested activities for students

1. Test a rule-based sorter

Choose a classroom-friendly task, such as sorting paper shapes by colour or shape. One student acts as the “system” and follows a rule chosen by the group. For example: “Put every shape with a curved edge in this pile.” Then test the rule on several shapes.

Ask: Was the rule clear? Did it work for every shape? What happened if a shape was difficult to classify? Explain that this is a simplified, offline activity, not a model of all AI. It can still prompt useful discussion about how a system follows instructions and where mistakes may occur.

2. Look for fairness in a made-up scenario

Use a clearly hypothetical example: a school designs a fictional computer system to suggest which books might interest students. The system’s suggestions are based on a small collection of books chosen by one class.

Ask students: Whose interests might be missing? Could some students receive fewer useful suggestions? What additional information or viewpoints would help? Emphasise that a small or unrepresentative set of examples can produce limited results. Students should explain their reasoning rather than label the imaginary system as definitely fair or unfair.

3. Map possible effects

Draw three columns on paper: “People”, “Society” and “Environment”. Pick a familiar type of AI use, such as a tool that recommends videos, and list possible benefits and concerns in each column. For example, a recommendation may help someone find relevant material, while also making it important to think about how recommendations shape what people see.

For the environment column, students can ask what resources may be needed to make and run digital services. Do not guess at amounts or assume that every service has the same impact. The useful habit is to notice the question and seek reliable information when it is available.

Prompts for deeper thinking

To move a discussion beyond “AI is good” or “AI is bad”, try these follow-up questions:

• Who made the decision about how the system should work?
• Who could explain or challenge a result if it seems wrong?
• What might happen if people rely on the result without checking it?
• What information would we need before reaching a conclusion?
• Is using AI necessary for this task, or could a simpler option work?

These questions introduce ideas such as governance—the way decisions and responsibility are organised—and proportionality: whether a tool or response is suitable for the situation. Students can discuss these ideas in everyday language before learning formal definitions.

How parents and teachers can support learning

• Invite students to explain how they reached a view, not just what their view is.
• Make room for uncertainty. “We do not know yet” can be a thoughtful answer.
• Compare different viewpoints respectfully, especially when a decision affects people differently.
• Use paper-based activities or teacher-supervised demonstrations. Children should not be asked to create accounts or share personal information with AI tools.
• Check age restrictions and school guidance before using any digital service.

A practical takeaway

AI ethics and sustainability can begin with ordinary questions about people, information, decisions and resources. Students who practise asking those questions are building critical thinking, data literacy and responsible technology habits. Start with one example, listen to different views and be clear about what is known—and what still needs checking.